Trying out world map

Creating a interactive choropleth world map

library(gapminder)
library(ggplot2)
library(plotly)

Attaching package: 'plotly'

The following object is masked from 'package:ggplot2':

    last_plot

The following object is masked from 'package:stats':

    filter

The following object is masked from 'package:graphics':

    layout

library(dplyr)

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

library(ggthemes)
library(RColorBrewer)
library(crosstalk)
library(DT)

world <- map_data("world") %>%
  filter(region != "Antarctica")

Cleaning and processing of data, outputing top 5 rows

data <- read.csv("/private/test.csv")
head(data)

  X                          Country Fertility Population Test CountryCode
1 1                            Niger      6.82  24785.587  NER         NER
2 2                          Somalia     6.312  16801.170  SOM         SOM
3 3                             Chad     6.255  16910.218  TCD         TCD
4 4 Democratic Republic of the Congo     6.156  94374.379  COD         COD
5 5         Central African Republic     5.978   5414.014  CAF         CAF
6 6                             Mali     5.956  21561.299  MLI         MLI

data <- data %>%
  mutate(Fertility = as.numeric(as.character(Fertility)))

Warning: There was 1 warning in `mutate()`.
ℹ In argument: `Fertility = as.numeric(as.character(Fertility))`.
Caused by warning:
! NAs introduced by coercion

head(data)

  X                          Country Fertility Population Test CountryCode
1 1                            Niger     6.820  24785.587  NER         NER
2 2                          Somalia     6.312  16801.170  SOM         SOM
3 3                             Chad     6.255  16910.218  TCD         TCD
4 4 Democratic Republic of the Congo     6.156  94374.379  COD         COD
5 5         Central African Republic     5.978   5414.014  CAF         CAF
6 6                             Mali     5.956  21561.299  MLI         MLI

Baseline code for the Map

# Set figure dimensions
#| fig.width=7
#| fig.height=5



# Display all Brewer palettes
display.brewer.all()

# Filter Gapminder data and join with world map data
  mapa_animado_3 <- data %>%
  right_join(world, by = c(Country = "region")) %>%
  ggplot(aes(long, lat, group = group, fill = `Fertility`)) +
  geom_polygon(color = "white", size = 0.01) +
  theme_void() +
  scale_fill_distiller(palette = "Spectral", name = "Fertility Rate") + # Use a continuous palette
  labs(title = "Population & Fertility Rate", subtitle = "year: 2022")  +
  theme(
    plot.title = element_text(size = 12, hjust = 0.5),
    plot.subtitle = element_text(size = 10, hjust = 0.5),
    plot.caption = element_text(size = 8, hjust = 1)
  ) +
  coord_fixed(ratio = 1.3)

Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
ℹ Please use `linewidth` instead.

# Convert ggplot object to a ggplotly object
fig_3 <- ggplotly(mapa_animado_3)

fig_3

Trying to add hovertext with data and data Frame

# Assuming 'world' and 'data' are already loaded and prepared
# Create a hover text column in 'data'
data$hover_text <- paste("Country: ", data$Country, "<br>Fertility Rate: ", data$Fertility, "<br>Population: ", data$Population)

joined_data <- data %>%
  right_join(world, by = c(Country = "region"))

# Proceed with your plotting
mapa_animado_3 <- joined_data %>%
  ggplot(aes(x = long, y = lat, group = group, fill = Fertility, text = hover_text)) + # Added 'text' aesthetic for custom hover info
  geom_polygon(color = "white", size = 0.01) +
  theme_void() +
  scale_fill_distiller(palette = "Spectral", name = "Fertility Rate") + # Use a continuous palette
  labs(title = "Population & Fertility Rate", subtitle = "year: 2022")  +
  theme(
    plot.title = element_text(size = 12, hjust = 0.5),
    plot.subtitle = element_text(size = 10, hjust = 0.5),
    plot.caption = element_text(size = 8, hjust = 1)
  ) +
  coord_fixed(ratio = 1.3)

# Convert ggplot object to a ggplotly object with hoverinfo
fig_3 <- ggplotly(mapa_animado_3, tooltip = "text") # Specify 'text' to use the 'text' aesthetic for the tooltip
fig_3

displaying my joined_data into a dataframe and remove repeated country names

joined_data <- joined_data %>%
  distinct(Country, .keep_all = TRUE)

datatable(joined_data, options = list(autoWidth = TRUE))